Cleaner shrimp use a to advertise cleaning rocking dance service to clients

Signals transmit information to receivers about sender attributes, increase the fitness of both parties, and are selected for in cooperative interactions between species to reduce conflict [1, 2]. Marine cleaning interactions are known for stereotyped behaviors [3-6] that likely serve as signals. For example, dancing and tactile dancing in cleaner fish may serve to advertise cleaning services to client fish [7] and manipulate client behavior [8], respectively. Cleaner shrimp clean fish [9], yet are cryptic in comparison to cleaner fish. Signals, therefore, are likely essential for cleaner shrimp to attract clients. Here, we show that the yellow-beaked cleaner shrimp [110] Urocaridella sp. c [11] uses a stereotypical side-to-side movement, or rocking dance, while approaching potential client fish in the water column. This dance was followed by a cleaning interaction with the client 100% of the time. Hungry cleaner shrimp, which are more willing to clean than satiated ones [12], spent more time rocking and in closer proximity to clients Cephaiopholis cyanostigma than satiated ones, and when given a choice, clients preferred hungry, rocking shrimp. The rocking dance therefore influenced client behavior and, thus, appears to function as a signal to advertise the presence of cleaner shrimp to potential clients.

Species accumulation curves and their applications in parasite ecology

Species accumulation curves (SACs) chart the increase in recovery of new species as a function of some measure of sampling effort. Studies of parasite diversity can benefit from the application of SACs, both as empirical tools to guide sampling efforts and predict richness, and because their properties are informative about community patterns and the structure of parasite diversity. SACs can be used to infer interactivity in parasite infra-communities, to partition species richness into contributions from different spatial scales and different levels of the host hierarchy (individuals, populations and communities) or to identify modes of community assembly (niche versus dispersal). A historical tendency to treat individual hosts as statistically equivalent replicates (quadrats) seemingly satisfies the sample-based subgroup of SACs but care is required in this because of the inequality of hosts as sampling units. Knowledge of the true distribution of parasite richness over multiple host-derived and spatial scales is far from complete but SACs can improve the understanding of diversity patterns in parasite assemblages.

Precision-recall operating characteristic (P-ROC) curves in imprecise environments

Traditionally, machine learning algorithms have been evaluated in applications where assumptions can be reliably made about class priors and/or misclassification costs. In this paper, we consider the case of imprecise environments, where little may be known about these factors and they may well vary significantly when the system is applied. Specifically, the use of precision-recall analysis is investigated and compared to the more well known performance measures such as error-rate and the receiver operating characteristic (ROC). We argue that while ROC analysis is invariant to variations in class priors, this invariance in fact hides an important factor of the evaluation in imprecise environments. Therefore, we develop a generalised precision-recall analysis methodology in which variation due to prior class probabilities is incorporated into a multi-way analysis of variance (ANOVA). The increased sensitivity and reliability of this approach is demonstrated in a remote sensing application.